{"id":802522,"url":"https://alion.io/job/nttdata-aivista-ai-scientist-intern","title":"AI Scientist - Intern","company":{"id":679553,"name":"NTT DATA AIVista","domain":"nttdata-aivista.com","url":"https://alion.io/company/nttdata-aivista","size_band":null,"is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"intern","employment_type":"internship","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":160000,"max_usd":429000,"period":"year","method":null,"sample_n":3649},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Context Engineering","optional":false},{"name":"Digital Twin","optional":false},{"name":"Function Calling","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Interpretability","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-08-03T20:09:36Z","employer_posted_date":"2026-08-03","last_verified_at":"2026-09-24T17:12:30Z","board_verified":true,"closed_at":null,"days_open":51,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":51},"description":"AI Scientist Intern\nPalo Alto, California | 3-6 months\nAbout AIVista\nNTT DATA AIVista, Inc., a wholly owned subsidiary of NTT DATA, develops AI products for enterprises operating in complex regulatory environments. Based in Palo Alto, we combine deep AI product expertise with NTT DATA's industry knowledge and systems-integration experience, working with NTT companies to deploy solutions for enterprise clients.\nThe Opportunity\nThis research internship is designed for advanced PhD candidates who want to tackle foundational problems at the intersection of machine learning, knowledge representation, formal methods, and enterprise systems. You will work with scientists and engineers to turn research ideas into trustworthy AI capabilities evaluated on production-scale systems and data.\nThe internship lasts 3-6 months, with the possibility of extension. Pursuing top-tier conference publications is highly encouraged, and projects are selected to support both rigorous research andpractical relevance.\nScience Focus\nNeurosymbolic methods and trustworthy reasoning: Combine learning-based and symbolic techniques to improve reliability, transparency, and alignment with domain constraints.\nKnowledge representation and semantic AI: Develop methods that help AI systems organize, connect, and reason over complex enterprise information.\nAdaptive and model-agnostic AI systems: Explore flexible approaches that integrate models, tools, context, and memory across diverse tasks and environments.\nDocument and multimodal intelligence: Improve how AI systems understand and reason over information expressed across text, documents, images, and other modalities.\nLearning from feedback: Develop methods that enable AI systems to improve safely and\neffectively from human and operational feedback.\nEvaluation, verification, and interpretability: Advance rigorous approaches to assessing AI\nreliability, robustness, safety, and transparency.\nAI for complex workflows: Explore how intelligent systems can support and improve multi-step enterprise processes while maintaining appropriate oversight and control.\nWhat You'll Do\nDefine research questions and develop algorithms, prototypes, and system designs across one or more focus areas.\nDesign rigorous experiments and benchmarks that measure correctness, robustness, calibration, privacy, latency, cost, and process outcomes.\nWork with scientists, engineers, and domain experts to turn enterprise data, policies, feedback, and operational constraints into research artifacts and deployable systems.\nDevelop inspectable AI systems and analyses that connect model and agent decisions to\nevidence, rules, and outcomes.\nMove promising research toward production through simulation and controlled evaluation, and contribute results to high-quality research publications.\nQualifications\nAdvanced PhD candidate in computer science, machine learning, artificial intelligence, or a related field.\nA strong research record or demonstrated publication trajectory in relevant areas.\nStrong foundations in machine learning, algorithms, and statistical methods.\nDeep experience in at least one of the following: language models, knowledge representation or graphs, formal methods, agentic systems, continual learning, multimodal learning, or process mining.\nProficiency in Python and experience designing and running rigorous empirical studies.\nPreferred\nExperience with neurosymbolic methods, autoformalization, formal verification, theorem\nproving, or constraint solving.\nExperience with ontology construction, knowledge graphs, entity resolution, graph learning, or graph-based retrieval.\nExperience with agent memory, context engineering, model routing or orchestration, planning, tool use, or multi-agent systems.\nExperience with continual, federated, or privacy-preserving learning; uncertainty calibration; human-in-the-loop systems; or regression-safe adaptation.\nFamiliarity with process mining, digital twins, simulation, workflow systems, or graduated- autonomy deployments.\nExperience with robust and scalable benchmarking, agentic environment construction, and complex task metric design.\nInterest in bridging foundational research with deployed AI systems in regulated or high-stakes domains.\nCompensation Details\nThe monthly compensation range for this role is $12,500-$14,500. Individual compensation is determined based on factors including education, experience, skills, qualifications, geographic location, and business needs. Eligible interns may receive relocation and housing assistance.\nNTT DATA AIVista is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, ancestry,\nsex, gender identity or expression, sexual orientation, age, disability, genetic information, marital status, military or veteran status,\nreproductive health decisions, or any other characteristic protected under applicable federal, state, or local law.","description_format":"text","description_chars":4929,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Artificial Intelligence","LLM & Generative AI","AI Agents"],"lifecycle":[{"event":"open","at":"2026-09-12T08:30:28Z"}],"liveness":{"score":9,"band":"cold","label":"Long shot","p_open":1,"p_active":0.324,"p_room":0.28,"age_days":51,"expected_fill_days":20,"reasons":["conf:3","win:tail","crowd:junior"],"computed_at":"2026-09-24T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/nttdata-aivista-ai-scientist-intern","json_url":"https://alion.io/job/nttdata-aivista-ai-scientist-intern.json","meta":{"generated_at":"2026-09-24T18:14:30Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}